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Parallel Processing

Parallel processing divides a computation into tasks that run simultaneously across multiple processors or machines. It is the core technique that makes big data processing feasible, as tasks that would take hours on a single machine can complete in minutes when distributed. Spark and Hadoop both use parallelism to handle large-scale data.

Visit the following resources to learn more:

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